Cloud computing developed from the need of private companies to recover their investment in compute grids by renting out spare cycles in off-peak times. Typical implementations in compute grids infrastructure often resulted in over-provisioned compute grids and spare cycles of compute power that were not being utilized. As the market for cloud compute resources has been established, more dedicated providers have emerged in commercial settings, such as Amazon EC2, Softlayer, and Rackspace to provide excess compute capacity to consumers. Others have specifically developed compute grids to offer such processing power to consumers both on an as needed basis and on a subscriptions based model. The development of compute marketplaces and the increase in the number of compute provides has limited some of the waste associated with excess compute capacity. However, even these dedicated providers also suffer from the need to over-provision physical resources to insure sufficient compute capacity for a given job at any given time.
As the market for cloud services has grown, providers have pushed to differentiate themselves based on price, reliability, manageability, platform and other factors and features. Typically consumers of cloud compute services, however, are not interested in these complexities. Consumers are often most concerned with getting their compute work done “as soon as possible,” “as cheaply as possible,” or within some time or price constraint. Thus, the identification of underlying capacities of given cloud compute systems overwhelms the typical consumer.